Effect of magnetic field and temperature on the voltage-current characteristics of YBCO superconductor

Voltage-current characteristics of YBCO superconductor was studied under magnetic field up to 0.4 T at different temperatures below T_c. The critical temperature decreases and the transition width broadens under magnetic field. V-I data below T_c were fitted to a power law expression V I^(T,B) in which (T,B) is found to decrease with increase of magnetic field and temperature, gradually approaching unity as T approaches T_c, being independent of magnetic field. Similarly, (T,B) approaches unity as magnetic field increases being independent of temperature.     

Near-Entropy Hotlink Assignments

Consider a rooted tree T of arbitrary maximum degree d representing a collection of n web pages connected via a set of links, all reachable from a source home page represented by the root of T. Each web page i carries a probability p _i representative of the frequency with which it is visited. By adding hotlinks—shortcuts from a node to one of its descendents—we wish to minimize the expected number of steps l needed to visit pages from the home page, expressed as a function of the entropy H(p) of the access probabilities p. This paper introduces several new strategies for effectively assigning hotlinks in a tree. For assigning exactly one hotlink per node, our method guarantees an upper bound on l of 1.141H(p)+1 if d>2 and 1.08H(p)+2/3 if d=2. We also present the first efficient general methods for assigning at most k hotlinks per node in trees of arbitrary maximum degree, achieving bounds on l of at most \frac2H(p)log(k+1)+1\frac{2H(p)}{\log(k+1)}+1 and \fracH(p)log(k+d)-logd+1\frac{H(p)}{\log(k+d)-\log d}+1 , respectively. All our methods are strong, i.e., they provide the same guarantees on all subtrees after the assignment. We also present an algorithm implementing these methods in O(nlog n) time, an improvement over the previous O(n ²) time algorithms. Finally we prove a Ω(nlog n) lower bound on the running time of any strong method that guarantee an average access time strictly better than 2H(p).     

A tabu search with an oscillation strategy for the discriminant analysis problem

This article proposes a tabu search approach to solve a mathematical programming formulation of the linear classification problem, which consists of determining an hyperplane that separates two groups of points as well as possible in ?^m. The tabu search approach proposed is based on a non-standard formulation using linear system infeasibility. The search space is the set of bases defined on the matrix that describes the linear system. The moves are performed by pivoting on a specified row and column. On real machine learning databases, our approach compares favorably with implementations based on parametric programming and irreducible infeasible constraint sets. Additional computational results for randomly generated instances confirm that our method provides a suitable alternative to the mixed integer programming formulation that is solved by a commercial code when the number of attributes m increases.     

Approximation by Stancu–Chlodowsky polynomials

In this paper, we investigate convergence and approximation properties of a Chlodowsky type generalization of Stancu polynomials (we called Stancu–Chlodowsky polynomials).The rates of convergence of this generalization are obtained by means of modulus of continuity and by using the $K$-functional of Peetre. We also present and prove theorems on weighted approximation and the order of approximation of continuous functions by these operators on all positive semi-axis.     

Inspection strategy for availability improvement

In this paper, an inspection strategy is proposed for systems subject to random shocks and whose state is only known through inspection. The shocks magnitudes and times between shocks arrivals are random variables. Each shock induces an amount of damage to the system which is gradually weakened as damage accumulates. The system fails when the total damage exceeds some threshold level. The proposed inspection strategy suggests to inspect the system at predetermined times T₁, T₂,...T _k . If failure is detected, then the system is repaired to a state as good as new, otherwise, it is kept operating. The expression of the system availability is derived. A numerical procedure is developed to generate an inspection sequence which maximizes the system availability. The proposed strategy has been developed for some critical subsystems of trees harvesters. An illustrative example is provided.     

Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation

In this study, we experiment with several multiobjective evolutionary algorithms to determine a suitable approach for clustering Web user sessions, which consist of sequences of Web pages visited by the users. Our experimental results show that the multiobjective evolutionary algorithm-based approaches are successful for sequence clustering. We look at a commonly used cluster validity index to verify our findings. The results for this index indicate that the clustering solutions are of high quality. As a case study, the obtained clusters are then used in a Web recommender system for representing usage patterns. As a result of the experiments, we see that these approaches can successfully be applied for generating clustering solutions that lead to a high recommendation accuracy in the recommender model we used in this paper.     

A study of maintenance policies for second-hand products

This paper proposes two maintenance schemes for reused products. In order to reduce the purchasing cost or conform to the concept of environmental protection, reuse is considered as one of the most efficient strategies. However, the initial quality of reused product is often inferior to the new one and then product failures will occur frequently during usage period. Therefore, two periodical preventive maintenance (PM) policies in this paper are developed to decrease the high failure rate of the second-hand products. When a second-hand product with Weibull life time distribution of known age is intended to be used for a pre-specified period of time, the optimal number of PM actions and the corresponding maintenance degree are derived such that the expected total maintenance cost is minimized. The impact of providing preventive maintenance is illustrated through numerical examples.     

A low-order model of biological neural networks

A biologically plausible low-order model (LOM) of biological neural networks is proposed. LOM is a recurrent hierarchical network of models of dendritic nodes and trees; spiking and nonspiking neurons; unsupervised, supervised covariance and accumulative learning mechanisms; feedback connections; and a scheme for maximal generalization. These component models are motivated and necessitated by making LOM learn and retrieve easily without differentiation, optimization, or iteration, and cluster, detect, and recognize multiple and hierarchical corrupted, distorted, and occluded temporal and spatial patterns. Four models of dendritic nodes are given that are all described as a hyperbolic polynomial that acts like an exclusive-OR logic gate when the model dendritic nodes input two binary digits. A model dendritic encoder that is a network of model dendritic nodes encodes its inputs such that the resultant codes have an orthogonality property. Such codes are stored in synapses by unsupervised covariance learning, supervised covariance learning, or unsupervised accumulative learning, depending on the type of postsynaptic neuron. A masking matrix for a dendritic tree, whose upper part comprises model dendritic encoders, enables maximal generalization on corrupted, distorted, and occluded data. It is a mathematical organization and idealization of dendritic trees with overlapped and nested input vectors. A model nonspiking neuron transmits inhibitory graded signals to modulate its neighboring model spiking neurons. Model spiking neurons evaluate the subjective probability distribution (SPD) of the labels of the inputs to model dendritic encoders and generate spike trains with such SPDs as firing rates. Feedback connections from the same or higher layers with different numbers of unit-delay devices reflect different signal traveling times, enabling LOM to fully utilize temporally and spatially associated information. Biological plausibility of the component models is discussed. Numerical examples are given to demonstrate how LOM operates in retrieving, generalizing, and unsupervised and supervised learning.     

Exploiting information extraction techniques for automatic semantic video indexing with an application to Turkish news videos

This paper targets at the problem of automatic semantic indexing of news videos by presenting a video annotation and retrieval system which is able to perform automatic semantic annotation of news video archives and provide access to the archives via these annotations. The presented system relies on the video texts as the information source and exploits several information extraction techniques on these texts to arrive at representative semantic information regarding the underlying videos. These techniques include named entity recognition, person entity extraction, coreference resolution, and semantic event extraction. Apart from the information extraction components, the proposed system also encompasses modules for news story segmentation, text extraction, and video retrieval along with a news video database to make it a full-fledged system to be employed in practical settings. The proposed system is a generic one employing a wide range of techniques to automate the semantic video indexing process and to bridge the semantic gap between what can be automatically extracted from videos and what people perceive as the video semantics. Based on the proposed system, a novel automatic semantic annotation and retrieval system is built for Turkish and evaluated on a broadcast news video collection, providing evidence for its feasibility and convenience for news videos with a satisfactory overall performance.     

Wirtschaftsinformatik zwischen Wissenschaft und Unternehmertum

One of the major success indicators for applied research sciences is the rate of transfer from research into practice. Only if concrete and economically successful products are derived from research results, such sciences can induce an impact. However, this process of innovation mandatorily needs entrepreneurship. Within the domain of business information systems, the two German enterprises SAP AG and IDS Scheer AG demonstrate that linking research and innovation is the key to lasting success in the information technology markets. German industry has significant disadvantages on the cost of human resources. Therefore it can be only successful with products that incorporate a high degree of innovation and that are consequently highly priced. But the invention of such products needs scientific research as a source of inspiration. Germany has a highly developed infrastructure of research facilities and organizations. However, they need to be better coordinated and aligned with business needs. Vice versa, enterprises need to actively approach the scientific community in order to clearly formulate their demand. Such a strategy needs changes on all sides. To achieve a change in the domain of science, it is necessary to change the profile of leading researchers, such as full professors. They should incorporate attributes of an entrepreneur and be profiled more as a research manager that tries to anticipate future needs and to develop its unit in terms of research subjects as well as personnel and financial resources. Consequently, the process of application, selection and review of leading researchers should be more oriented on processes that are common in enterprises. E. g. external head-hunters can be involved in the searching and assessing process in order to get the best qualified person for the research vacancy. Also enterprises need to change their attitude towards scientific research. In order to foster this process, executives could be invited to advisory and supervisory boards of research organisations. Furthermore, those executives must be proactively informed about the research activities and results in order to attract their interest and to show potentials for a transfer into products. There is still a long way in the hunt for innovation leadership and all these suggestions can only be a starting point.